AI

Nesa (NES) is an AI infrastructure network designed for privacy-preserving, verifiable computing and decentralized execution. Leveraging Equivariant Encryption (EE), HSS-EE, and a distributed inference architecture, it allows AI models to perform inference tasks without exposing data or model content.

NES is the native token of the Nesa decentralized AI network, primarily used to pay for AI inference fees, node staking, network governance, and ecosystem incentives. As a critical component of network operations, NES not only facilitates value transfer but also connects developers, node operators, and the broader AI infrastructure ecosystem.

Both Nesa and the OpenAI API offer AI inference capabilities for developers, but they operate under fundamentally different service models. The OpenAI API is built around centralized cloud services, whereas Nesa builds an AI execution layer via a decentralized network, private inference, and verifiable computation.

Samsung SDI, a core battery and energy storage subsidiary of South Korea's Samsung Group, operates across power batteries, energy storage systems (ESS), and advanced electronic materials. It occupies a critical industry position amid rising demand for energy storage from global electric vehicles and AI data centers. With Gate's introduction of Korean stock trading, investors can now use USDT to directly trade KOSPI-listed new energy assets, enabling unified cross-market allocation and strategic investment in the global energy chain.

SK hynix, a global leader in memory chip manufacturing, plays a key role as a high-performance memory supplier in the AI supply chain. Its core products—DRAM, HBM (High Bandwidth Memory), and enterprise-grade SSDs—are widely deployed in AI chips, GPU servers, cloud computing platforms, and large data centers.

SK hynix and Micron Technology are two of the three core memory chip manufacturers worldwide, having long dominated the DRAM, NAND Flash, and enterprise storage markets. As demand for artificial intelligence, large model training, and data centers grows, both companies are actively expanding their presence in the HBM (High Bandwidth Memory) market to serve the high-speed memory needs of AI GPUs.

South Korea is a critical hub in the global semiconductor industry, with a longstanding leadership in memory chips. Samsung Electronics and SK Hynix together command the global market for DRAM, NAND Flash, and HBM (High Bandwidth Memory), positioning South Korea as a key supply center for AI storage infrastructure. In contrast to China's Taiwan region, which excels in wafer foundry, South Korea's semiconductor sector emphasizes memory chip research, development, and manufacturing. The industry encompasses not only memory chip manufacturers but also equipment suppliers, material producers, packaging and testing firms, and a wafer foundry ecosystem.

OKZOO collects real-world data—such as air quality, temperature, humidity, and noise—via its P-mini environmental sensing device, then uploads the data to a decentralized network for verification and recording. A full data upload process typically involves six stages: environmental data collection, device preprocessing, network verification, on-chain recording, AI data integration, and reward distribution. Unlike traditional IoT networks, OKZOO integrates data contribution, on-chain incentives, and AI use cases, enabling real-world data to continuously become verifiable digital assets and AI resources.

The core distinction between OKZOO and traditional DePIN projects lies in the type of resources the network produces and utilizes. Traditional DePIN projects center on infrastructure resources like hashrate, communication networks, bandwidth, or geolocation. In contrast, OKZOO focuses on environmental data collection and AI data infrastructure. Through P-mini devices, OKZOO gathers real-world environmental data and combines AI Pet and AIOT incentive mechanisms to build an AIoT network.

OKZOO (AIOT) is an AIoT infrastructure integrating AI, IoT, and blockchain networks, collecting real-world data through distributed environmental sensing devices and leveraging AI Pet interaction mechanisms and AIOT tokens to incentivize user data contributions. OKZOO aims to build a global environmental data network, providing trustworthy, Tiempo real, and verifiable data sources for AI models, smart devices, and real-world applications.

Portal's AI Agent workflow is a game development system powered by multiple AI agents working in tandem, capable of turning creators' creative descriptions into playable game products step by step. The entire process typically covers requirements understanding, game design, asset generation, logic building, automated testing, and content publishing. Each agent handles specific tasks and coordinates with others through a centralized orchestration system.

Portal (PORTAL) is an AI-native game creation platform built for game developers and content creators. Leveraging AI agents, automated content generation tools, and creator-first workflows, it unifies and automates the full game development pipeline — from concept and asset creation to testing and release. Portal's goal is to reduce the technical barriers to game development, allowing more individual creators to participate in game development using natural language and AI tools.

Prompt-to-Game is a development methodology that leverages generative AI to directly transform natural language prompts into game content. Creators simply input descriptions of characters, scenes, gameplay mechanics, or narrative backgrounds, and the AI system automatically generates game assets, interaction logic, and foundational gameplay frameworks, dramatically reducing the barrier to entry for game development. Portal positions Prompt-to-Game as a core component of its AI Native game creation ecosystem, handling requirement analysis, game design, asset generation, logic development, and automated testing through the coordinated efforts of multiple AI Agents.

The AI Agent within AIVIVE is an intelligent agent system equipped with goal comprehension, sustained execution, and automated feedback capabilities. Rather than simply responding to queries, it continuously performs analysis, decision-making, and execution aligned with task objectives.

AIVIVE (AVV) is an on-chain protocol network built around AI-powered consumption use cases. It connects user behavior with protocol operations via cross-chain infrastructure, automated execution systems, and a verifiable economic cycle. The project introduces the Recursive AI Protocol (RAP) concept, aiming to establish a new AI consumption model driven by real-world usage — one that lets protocols evolve based on actual interactions.